We employ the joint production decomposition model to conduct a full decomposition of CO2 emission among 36 industrial sectors in China from 1998 to 2011, under the framework of growth accounting. The results show that: (1) the average CO2 emission increases at an annual rate of 3.01%, and production technology progression is the main driving force, while the transformation toward clean production effectively curb the rapid growth of CO2 emissions; (2) the effect of technology changes on CO2 emission is larger during the "10th Five-Year Plan" compared with the "11th Five-Year Plan", which makes the annual growth rate of CO2 emission during the "11th Five-Year Plan" 1% lower than its counterpart; This study has important theoretical and practical significance for understanding the driving factors of CO2 emission and the corresponding emission reduction measures.

A differences-in-differences (DID) model and financial data from Chinese listed firms from 2011 to 2019 are used to empirically investigate the effects of the digital economy on corporate financial asset holdings using the "Broadband China" policy as a quasi-natural experiment. After robustness testing and heterogeneity effects are disposed of, the digital economy dramatically boosts corporate financial asset holdings. According to the channel analysis, the digital economy can reduce corporate financing constraints and boost corporate financial asset holdings, notably based on speculative demand. Heterogeneity analysis shows that the digital economy has a greater impact on corporate financial asset holdings for firms with higher market competition, small-scale firms with a short-listed age, and firms in the western region. This paper provides policy guidance for enterprises returning to the real economy.

This paper uses the questionnaire data of the World Bank’s China Enterprise Survey 2012 to establish a Logit model to empirically study the relationship between knowledge sources and technological innovation in Chinese manufacturing enterprises. The results show that although internal and external knowledge has a positive effect on enterprise technological innovation in general, there are significant differences when taking the types of innovation, subject characteristic and the types of cooperation into consideration. From the current development stage of China's manufacturing enterprises, external knowledge sources, external enterprise knowledge subjects, and employee knowledge have a more positive effect on technological innovation, which also shows that the role of technical employees on technological innovation has a significant threshold effect, and only after a certain degree of accumulation can internal technical employees have a more significant positive effect on technological innovation.

This paper uses China Household Income Project rural household survey data spanning 30 years (1988-2018) to study the impact of China’s industrialization on rural household income. In the semiparametric regression model, we use the rural households’ distance to the manufacturing hub to analyze the spillover effect of industrialization on their income and the spatial attenuation. The results show that the income gap between rural households in Guangdong and other provinces increased from 1988 to 2002, but continuously decreased from 2002 to 2018; the rural households’ distance to the Pearl River Delta or the Yangtze River Delta, the two international manufacturing hubs, has a significant impact on their income, which has been increasing from 1988 to 1995, but has been decreasing since the new century. On the contrary, the influence of the rural households’ distance to the provincial capital on their income has been increasing since the new century.

This paper describes two novel approaches to cost estimation of manufactured products where a data set of similar products have known manufactured costs. The methods use the notion of piecewise functions and are (1) clustering and (2) splines. Cost drivers are typically a mixture of categorical and numeric data which complicates cost estimation. Both clustering and splines approaches can accommodate this. Through four case studies, we compare our approaches with the often-used regression models. Our results show that clustering especially offers promise in improving the accuracy of cost estimation. While clustering and splines are slightly more complex to develop from both a user and a computational perspective, our approaches are packaged in an open-source software. This paper is the first known to adapt and apply these two well-known mathematical approaches to manufacturing cost estimation.

In this paper, we develop a model in which a monopolistic firm manufactures and sells a digital product, by incorporating digital rights management (DRM), quality degradation of pirated products, and government copyright enforcement into the consumer’s utility function. We determine the monopolist’s optimal pricing strategies and the appropriate DRM protection level through mathematical deduction. Our results show that when the government copyright enforcement is moderate and the quality of pirated products is relatively high, implementing a DRM system is optimal for the monopolist. However, in most other cases, DRM-free is better for the monopolist. This result may explain why DRM is not very popular in some industries. Our results suggest that choosing the right price, focusing on content innovation, and weakening DRM protection may be a better strategy for firms now. The results also indicate that DRM-free may be more prominent in the digital music industry than in the software and video games industries.

Based on China's 30 provincial panel data from 2006 to 2018, this paper uses the spatial Durbin model to empirically study the influence path and transmission mechanism of financial development on regional technological innovation, and introduce digital finance environment, marketization degree, and government environmental management as an adjustment variable to verify its regulating effect on financial development and regional technological innovation. The study found that the overall promotion of digital finance to local technological innovation is not significant. Besides, the characteristics of ownership discrimination and weak risk appetite in the bank's medium and long-term credit market have led to its failure to promote regional technological innovation. In contrast, the stock market and bond market in direct financing channels have enhanced local innovation capabilities. When the external environmental system is used as the adjustment variable, the results show that an excellent digital finance development, marketization degree, and government environmental management can effectively and positively regulate the effect of financial development and technological innovation.

The construction and optimization of a portfolio is a complex process that has been a historically active research area in finance. For portfolios with highly correlated assets, the performance of traditional risk-based asset allocations methods such as the mean-variance (MV) model is limited when numerous assets are correlated. A novel clustering-based asset allocation method, called Hierarchical Risk Parity (HRP), provides an opportunity to mitigate these limitations in portfolio construction. HRP utilizes the hierarchical relationships between the covariance of assets in a portfolio to determine weight distributions, eliminating the need for the inversion of the covariance matrix that is required by most traditional risk-based asset allocation methods. This research examines the viability of Hierarchical Risk Parity (HRP) method in portfolio construction of a US equity portfolio and compares the performances of HRP to traditional asset allocation methods exemplified by the mean-variance (MV) method. The results of this research show that the performance of the HRP method is comparable to the performance of the MV method. Given these findings, HRP provides an advantageous approach for portfolio construction in practical scenarios where correlated assets are present in the portfolios.

Based on the income poverty level differences and multi-dimensional poverty perspective in China, this paper compares the performance of education poverty alleviation, employment poverty alleviation, and industry poverty alleviation. The hypothesis was tested by quantile regression and ordered probit model. The results show that: in the short term, the effect of poverty alleviation through education is not significant; however, the effect of poverty alleviation through employment and industry is significant, increasing the income of poor households to a certain extent. The effect of poverty alleviation through employment is high. In the long term, the effect of poverty alleviation through industry is good. For the deep poor households, the effect of poverty alleviation through employment is more significant in the short term. For the marginal poor, only industry poverty alleviation has a significant effect on poverty alleviation. Education poverty alleviation and industry poverty alleviation are conducive to improving multi-dimensional poverty. In the alleviation of multi-dimensional poverty, employment poverty alleviation and education poverty alleviation have a certain synergy.

The low-carbon city pilot is an important policy for promoting sustainable development and addressing climate change. The level of green technological innovation is a significant driving force for China's transition to high-quality development and the realization of carbon peaking and carbon neutrality goals. This essay takes the panel data of 30 provinces in China from 2008 to 2020 as the research sample, regards the number of urban green invention patent applications as a quantifiable indicator of the level of urban green technological innovation, and takes the policy of low-carbon city pilot as a quasi-natural experiment, and uses the difference-in-differences model to test the impact of low-carbon city pilot on the level of urban green technological innovation, and to investigate the mechanism of action within. The main conclusions are as follows: (1) The policy of low-carbon city pilot has an outstanding promotion effect on the level of urban technological innovation. (2) Using the mediating effect to analyze, it is found that the low-carbon city pilot policy can improve the level of urban green technological innovation through the development of green finance.

With the continuous advancement of technological revolution and industrial transformation, digital finance supported by big data and artificial intelligence has become an important engine for promoting carbon neutrality. We measured the industrial structure transformation index (ISU) of 30 provinces in China, and discussed the spatial spillover effect and transmission mechanism between digital finance and ISU using the spatial Durbin model. The research results demonstrate that the digital finance development can significantly improve the local ISU. Interestingly, the impact of digital finance on the ISU of adjacent areas has a significantly negative spatial spillover effect, which still exists under the different spatial weight matrix. Digital finance can improve ISU by improving green technology innovation, upgrading industrial structure, and alleviating capital allocation. We also found that the higher degree of marketization and environmental regulation can increase the positive influences of digital finance on ISU. This research proves the effectiveness of the digital finance in improving energy efficiency, and it encourages policymakers around the world to rely on digital finance to promote ecological governance and achieve high-quality economic development.

Based on the provincial panel data of China from 2011 to 2019 for a total of 9 years, this paper uses the entropy method to construct a comprehensive measure of the digital economy and common prosperity. We theoretically analyzed the impact mechanism of the digital economy on common prosperity using the econometric model. The study found that the digital economy can significantly promote the realization of common prosperity. The digital economy has a significant impact on the development and sustainability of common prosperity. The results of the impact mechanism show that the digital economy promotes common prosperity by increasing entrepreneurial activity. Heterogeneity research shows that the role of digital economy in promoting common prosperity changes with different regions. Specifically, the digital economy in the central and western regions can significantly promote the realization of common prosperity, but this impact is not significant in the eastern region. From the regression results of the digital economy, we can see that industrial digitalization and digital infrastructure play a greater role in promoting common prosperity. Economic openness affects the promotion of digital economy to common prosperity. The conclusion of this work provides an important research reference for the development of digital economy and the realization of common prosperity.

The signing of RCEP has created new opportunities for the development of China's export trade, and international logistics capacity is an important factor affecting the conduct of international trade. This paper qualitatively describes and analyzes the LPI index and its sub-indicators of RCEP member countries, and empirically investigates the impact of logistics performance level on China's export trade through an extended gravity model. The study shows that there are large differences in logistics performance levels among RCEP member countries, especially in South Asia, where the quality of logistics infrastructure and customs efficiency are the most lagging behind, which are the key factors pulling down the logistics performance index; the signing of RCEP has effectively promoted China's foreign trade level, but there are great differences in export amounts to different countries, and the logistics performance levels of importing countries and China's export trade are significant positive correlation, the improvement of logistics performance is conducive to promoting China's export trade to RCEP member countries, and from the viewpoint of logistics links, the role of logistics infrastructure quality is the strongest, and the influence of cargo transportation timeliness is the weakest.

Bank capital requirements would entail large social costs if they made resource allocation suboptimal and banking services costly by unduly limiting the banks’ ability to lend. This paper considers three main factors that may make capital requirements relevant, namely, deposit insurance subsidies, stock valuation errors, and tax shields derived from debt financing. The theoretical model analyzes the combined effects of the three factors on the banks’ incentives to make fairly priced loans, which should also be socially optimal loans. A key finding is that the long-term cost of capital requirements is likely to be very small when deposit insurance is underpriced. Increased funding costs resulting from higher capital requirements are absorbed by shareholders of banks, rather than passed on to borrowers. Under some reasonable assumptions, higher capital requirements improve resource allocation by countervailing distortionary effects of deposit insurance subsidies. Short-term adjustment costs can still be large, but it should be relatively easy to mitigate the short-term effects.

This research investigates the determinants of women's empowerment within households in a developing country. The investigation specifically focuses on the impact of employment and fertility, considering constraints imposed by family rules that play a pivotal role in shaping women's empowerment. The theoretical framework outlined in this study posits a simplistic model demonstrating that, within the prevailing family structure and household composition, earned income and fertility may bear significant relevance. Utilizing data extracted from the Pakistan Social and Living Standards Measurement Survey, we engage in estimating the level of female empowerment, operationalized as the extent of female authority over household expenditures. Notably, our empirical approach accounts for the endogeneity of employment and fertility through a two-stage estimation process. This involves leveraging information on family rules—representative of a family's cultural norms—pertaining to work and childbearing. Our empirical findings affirm the viability of family-specific rules as instruments to estimate and subsequently predict employment and fertility. Importantly, the evidence gleaned underscores the critical role of selecting valid threat options in theoretical analyses of women's empowerment.

Electricity price volatility in developing economies, particularly Nigeria, presents a significant challenge to sustainable development. In this paper, we examine the macroeconomic drivers of electricity prices (ELP) in Nigeria based on annual data spanning 1980-2022 and the autoregressive distributed lag (ARDL) procedure. Our model estimates the long-run and short-run impacts of population growth (PG), economic growth (GDP), crude oil price (COPR), and electricity consumption (ELC) on electricity prices (ELP). The empirical findings reveal a positive and long-run effect of PG on ELP, indicating that rising demand from a growing population increases electricity prices. In the short-run, ELC surprisingly co-moved with ELP, which may be attributable to price-sensitive demand within specific consumer segments or periods. Furthermore, GDP and COPR exert positive effects on ELP, indicating that economic growth drives energy consumption and prices, and the cost-driven impact of fossil fuel dependence in electricity generation. These findings shed light on the complex interplay of demographic, economic, and energy market-related forces driving electricity prices in Nigeria. Therefore, the paper proposes some policy suggestions based on the empirical findings.

The digital transformation provides an opportunity for the development of a green and low-carbon economy. This study used panel data collected from 30 Chinese provinces between 2011 and 2018, and assessed the impact of digitization (Dig) on environmental efficiency (EE). Quantile regression is employed to scrutinize the evolution of the marginal effect. From the perspectives of population and institutional factors, this study empirically investigates nonlinear relationships and potential mechanisms using Hansen threshold and mediation models. The findings reveal several key insights. Overall, levels of digitization and environmental efficiency (EE) are increasing with regional dispersion expansion, indicating a “polarization” characteristic. The impact of digitization on EE exhibits noticeable stage and regional heterogeneity. Analysis of population factors reveals that population structure, population size, and human capital trigger a sharp “marginal increase” of positive effects with single thresholds of 0.8155, 7.2284, and 11.0497, respectively. Analysis of institutional factors highlights the significance of fiscal policy quality (tax proportion), education expenditure, and tax system structure as important intermediaries. Finally, this paper presents corresponding policy implications.

The use of cloud computing by firms can be expected to go hand in hand with higher productivity, more innovations, and lower costs, and, therefore, should be positively related to export activities. Empirical evidence on the link between cloud computing and exports, however, is missing. This paper uses firm level data for manufacturing enterprises from the 27 member countries of the European Union taken from the Flash Eurobarometer 486 survey conducted in February – May 2020 to investigate this link. Applying standard parametric econometric models and a new machine-learning estimator, Kernel-Regularized Least Squares (KRLS), we find that firms which use cloud computing do more often export, do more often export to various destinations all over the world, and do export to more different destinations. The estimated cloud computing premium for extensive margins of exports is statistically highly significant after controlling for firm size, firm age, patents, and country. Furthermore, the size of this premium can be considered to be large. Extensive margins of exports and the use of cloud computing are positively related.

Based on provincial panel data in China, this study is the first to investigate whether industry-university-research collaborative innovation (IURCI) can help to improve factor misallocation. It is found that IURCI can significantly improve capital misallocation and labor misallocation, and the effect has regional differences, which shows that the improvement effect is obvious in areas with factor under-allocation, such as the central and western regions, but not obvious in areas with factor over-allocation, which conforms to the rule of diminishing marginal returns. A regulatory effect model is built to explore the impact of regional heterogeneity, through which we find that after considering three external environmental conditions, including economic development level, academic research level, and marketization degree, the improvement effect of IURCI on factor misallocation undergoes significant changes. The research results show that to deepen the marketization reform of factor allocation, we can start with IURCI. The government should form a sustainable and normalized industry-university-research collaborative innovation ecological mode through pilot cases and adopt measures according to local conditions to ensure the efficient use and reasonable distribution of capital and human resources of enterprises, universities, and scientific research institutions.

This paper explores the transformative journey from traditional e-commerce to the emerging realm of virtual commerce (v-commerce) within the metaverse, a collective virtual shared space created by the convergence of virtually enhanced physical reality and physically persistent virtual reality. The metaverse, with its immersive and interactive capabilities, is reshaping the landscape of economic activities, creating a paradigm shift in the way consumers shop, sell, and buy goods and services. The study delves into the impact of virtual reality (VR) technologies on consumer behavior, business models, and the overall economy. It investigates how VR is revolutionizing the shopping experience by offering immersive, personalized, and interactive platforms, thereby influencing con-sumer decision-making processes. The paper further examines the implications of these changes for businesses, particularly in terms of strategy, operations, and customer engagement. Moreover, the paper discusses the challenges and opportunities presented by the metaverse economy, including issues related to privacy, security, digital divide, and regulatory frameworks. It also highlights the potential of v-commerce to drive economic growth, innovation, and sustainability in the digital age. The paper concludes with a discussion on the future directions of v-commerce and the potential strategies for businesses to thrive in this new economic landscape.